Automatic analysis of a skull fracture based on image content

Author(s):  
Hong Shao ◽  
Hong Zhao
1994 ◽  
Vol 33 (01) ◽  
pp. 157-160 ◽  
Author(s):  
S. Kruse-Andersen ◽  
J. Kolberg ◽  
E. Jakobsen

Abstract:Continuous recording of intraluminal pressures for extended periods of time is currently regarded as a valuable method for detection of esophageal motor abnormalities. A subsequent automatic analysis of the resulting motility data relies on strict mathematical criteria for recognition of pressure events. Due to great variation in events, this method often fails to detect biologically relevant pressure variations. We have tried to develop a new concept for recognition of pressure events based on a neural network. Pressures were recorded for over 23 hours in 29 normal volunteers by means of a portable data recording system. A number of pressure events and non-events were selected from 9 recordings and used for training the network. The performance of the trained network was then verified on recordings from the remaining 20 volunteers. The accuracy and sensitivity of the two systems were comparable. However, the neural network recognized pressure peaks clearly generated by muscular activity that had escaped detection by the conventional program. In conclusion, we believe that neu-rocomputing has potential advantages for automatic analysis of gastrointestinal motility data.


2008 ◽  
Vol 67 (19) ◽  
pp. 1777-1790 ◽  
Author(s):  
C. Cruz-Ramos ◽  
R. Reyes-Reyes ◽  
J. Mendoza-Noriega ◽  
Mariko Nakano-Miyatake ◽  
Hector Manuel Perez-Meana

Author(s):  
Phichayasini Kitwatthanathawon ◽  
Thara Angskun ◽  
Jitimon Angskun

2018 ◽  
Vol 9 (1) ◽  
pp. 24-31
Author(s):  
Rudianto Rudianto ◽  
Eko Budi Setiawan

Availability the Application Programming Interface (API) for third-party applications on Android devices provides an opportunity to monitor Android devices with each other. This is used to create an application that can facilitate parents in child supervision through Android devices owned. In this study, some features added to the classification of image content on Android devices related to negative content. In this case, researchers using Clarifai API. The result of this research is to produce a system which has feature, give a report of image file contained in target smartphone and can do deletion on the image file, receive browser history report and can directly visit in the application, receive a report of child location and can be directly contacted via this application. This application works well on the Android Lollipop (API Level 22). Index Terms— Application Programming Interface(API), Monitoring, Negative Content, Children, Parent.


2013 ◽  
Vol 40 (2) ◽  
pp. 188
Author(s):  
Hai-Ning ZHANG ◽  
Wen-Ming HUANG ◽  
Jia-Jun FU ◽  
Xiang-Ping XU ◽  
Tao XU

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